The present disclosure is related to structure design and exploration, revision, optimization, and similar actions with regard to such designs, and more specifically to systems and methods for understanding structure design (e.g., program details) and its context (e.g., location details), extracting from actions and environments user intentions and preferences, predicting future actions and preferences, comparing structure designs, and otherwise assisting in the structure design process.
Traditionally, the process of designing and building a structure involves many professionals with many different skill sets. As an example, a developer interested in having a commercial structure built may retain an architect, who takes the developer's requirements and preferences, details about the site, building codes and the like, and first generates a conceptual design, then a more detailed schematic design. At this stage, the architect's role is to synthesize, problem solve, and design. The resulting forms, as drawn and/or modeled, are typically a blending of art and engineering. Reviews and reworking for multiple different audiences typically occur next in what is often referred to as design development. For example, an architectural engineer or similar professional may review the design and plans for the proposed structure's integrity and safety, the developer may have input for modifications to the design to meet a desired design goal, the builder may introduce limitations based on cost, time-to-completion, feasibility, and so on.
Portions of the design may also be sent to sources for cost estimates and to determine availability of elements of the structure, estimates for labor cost and time-to-delivery of components, etc. Estimates, as well as potential design modifications, from these many other sources may then also be factored into the structure design, cost, calculated time-to-completion, and so on. Bidding and negotiation may take place, such as with a builder or construction manager, parts and services providers, etc. Further design development then typically takes place to bring the design in-line with budgets, evolving design requirements, etc.
Once the final design and plans converge for the main parties of interest (developer, architect, engineer, and builder, who form the core of the ecosystem for the project), required permits and other approvals may then be sought. An additional one or more round(s) of design development take place including negotiations with certifying and permitting agencies in order to converge on a mutually acceptable design. Ultimately, construction begins and in spite of inevitable design change orders (and associated cost and time overruns) a structure is built.
While there are many other steps and parties involved, and the actual order of things may vary from structure to structure, the process is long, convoluted, circular, often unnecessarily complex, with many parties involved, and there are many opportunities for inefficiencies and delays in the various design, interaction, revision, and iteration of the design and build process. Furthermore, for each new structure, the process essentially reinvents itself from scratch, but never the same from one structure to the next. There is little re-use of designs, processes, and data in the design and construction of new structures. And, there are few resources available to improve efficiency and effectiveness in the communication and work processes taking place in the community of people and agencies involved in the design and construction process.
To this end, a number of systems have been proposed that, very broadly, modularize structure design. See, for example, the aforementioned U.S. Patent Application titled “System and Methods for Structure Design, Analysis, and Implementation”, Ser. No. 13/112,727. According to that disclosure, a computer-implemented system for designing a structure and coordinating its implementation includes a design workspace, a design engine which receives various inputs and produces a structure design for display in the design workspace, a set of design requirement rules for producing the structure design, and a cell source providing a definition of a cell that forms a unit of the structure design. The cell definition may be instantiated as a plurality of cells that are assembled together with other cells to form the structure design. An attributes engine quantifies measures of various attributes of a structure based on the structure design during the process of designing the structure, and displays the quantified measures in a dashboard user interface. An optimization engine analyzes the structure design, and proposes alternative designs in an effort to improve the design from the perspective of one or more attributes, including the attributes quantified by the attributes engine.
While an automated system has been disclosed that simplifies the structure design process in many regards, the disclosed methods still leave it largely to the user to explore design options and make appropriate design choices, and to do so often from first principles for each structure being designed. There remains a need to provide improved design choice assistance to a user in the context of creating a structure design. There also remains a need for systems and methods that assist a user in the design process, particularly retaining knowledge about design choices from one design to the next. Existing design strategies also leaves it to groups of designers (and other interested parties) to coordinate their efforts in producing a cohesive design that seeks to meet the requirements of a potentially large number of individuals and groups. Accordingly there remains a need for assisting groups in coordinating their design choices. Furthermore, while the system disclosed in the aforementioned U.S. patent application Ser. No. 13/112,727 can provide optimization options, and evaluate those options for different criteria, there remains a need for techniques for learning from past optimizations in order to provide more rapid convergence on an optimized design, avoid local maxima and other hurdles to optimization, avoid undesired optimizations, and so on. Still further, there is an unfilled need for convenient, consistent, and accurate methods for comparing multiple designs in order to extract similarities and other data therefrom, extract optimal design choices, and make that data available for meaningful use.